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检索条件"任意字段=4th International Conference on Computing and Data Science, CONF-CDS 2022"

共 1120 条记录，以下是351-360 订阅

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A Deep Learning-Based Human Action Recognition Based on Depth Maps, Skeletons, and Sensor Images 4

A Deep Learning-Based Human Action Recognition Based on Dept...

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4th international conference on Emerging Research in Electronics, Computer science and Technology, ICERECT 2022

作者： Rajput, Gaurav Kumar Lal Yadav, Ram Teerthanker Mahaveer University Department of Computing Science and IT Moradabad India Jaipur National University Department of Computer Sciences Jaipur India

ISBN: (纸本)9781665456357

this study describes a method for identifying human behavior based on depth motion maps. A depth video array projects each depth outline onto three symmetric Cartesian planes. A comprehensive depth video group forming a depth motion map, under each projection view he captures the unique differences between two successive projection maps. A 12-regularized joint representation classifier with a distance-weighted Tikhonov lattice is then applied for action detection. the developed method has been proven to be computationally efficient and capable of stepwise manipulation. Detection results using the Microsoft Exploration Action3D dataset show that our strategy performs more effectively than existing methods. Convolutional neural networks are used in this paper to offer a solution for human action recognition based on depth images and posture data (CNN). Both a depth motion image (DMI) and a proposed moving joint descriptor (MJD) are used as inputs for the purpose of action representation. © 2022 IEEE.

关键词： Convolutional neural networks

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University Indoor Scene Classification using Transfer Learning 4

University Indoor Scene Classification using Transfer Learni...

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Ramoliya, Dipak Goel, Parth Vaidya, Jinish Vadaliya, Poojan Computer Science & Engineering Department Anand Changa India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Image classification is used to classify images using a machine without any human intervention. this will help obtain all possible information of that particular capture just by feeding the image or by just clicking pictures from a device. the proposed study has created an extensive dataset of labs and its amenity by comprising 4502 images. Here there are 4 classes in the dataset: Apple Lab, Sophos Lab, Sophos Rack, and Virtual Reality Lab. the proposed work is based on transfer learning. data augmentation was performed after the proposed model was passed through VGG 16, ResNet50, Inception V3, and Xception pre-trained models from which features were extracted automatically and categorized into 4 distinct classes. Size of the model, inference time, training accuracy, testing accuracy, recall, precision, F1 score, and FLOPs were evaluated while analyzing through pre-trained models. Best experimental results were obtained using Xception pre-trained model among all 4 pre-trained network models with 99.90% as training accuracy, 99.75% as testing accuracy, 99.35% as recall, 99.85% as precision, and 99.60 % as F1 score;having a model size of 83 MB. © 2022 IEEE.

关键词： Image classification

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QoS-Aware Service Placement for Fog Integrated Cloud Using Modified Neuro-Fuzzy Approach 4th

QoS-Aware Service Placement for Fog Integrated Cloud Using M...

引用

4th international conference on Soft computing and its Engineering Applications (icSoftComp)

作者： Singh, Supriya Vidyarthi, D. P. Jawaharlal Nehru Univ Sch Comp & Syst Sci New Delhi 110067 India

ISBN: (纸本)9783031276088;9783031276095

Fog computing provides an infrastructure for enhancing quality of services (QoS), especially for time-critical applications. the reach of the Internet of things (IoT) has extended to another dimensions, expanding from acquisition of data to device interconnections and to data-processing. this acceleration assimilate fog and cloud compuhting into a single system for improving QoS and resource utilization. Due to the heterogeneity of IoT devices, selecting suitable computation devices and allocating resources are substantial issues that need to be addressed for effective resource utilization. this work proposes a smart decision-making system for service placement based on the various parameters. the proposed work utilizes machine learning based techniques: clustering for the labelling of the services followed by neuro-fuzzy based ANFIS model for offloading the services. A 5-layered neuro-fuzzy inference model is implemented to represent as an intelligent decisionmaking system. this work provides a solution for the learning phase of ANFIS by employing a meta-heuristic-based algorithm. three metaheuristic algorithms, i.e. GA-ANFIS, JAYA-ANFIS and PSO-ANFIS are implemented for the training of the ANFIS model. the effectiveness of the model has been examined for the prediction of computing layer for offloading of the services. the results are compared with each other as well as with the conventional gradient-based ANFIS model. Experiment shows that the evolutionary-based neuro-fuzzy models yield imperative results against gradient-based neuro-fuzzy.

关键词： Fog computing IOT Machine intelligence Neuro-fuzzy Resource provisioning

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SHAMan: A Versatile Auto-tuning Framework for Costly and Noisy HPC Systems 5th

SHAMan: A Versatile Auto-tuning Framework for Costly and Noi...

引用

4th international conference on Optimization and Learning (OLA)

作者： Robert, S. Zertal, S. Couvee, P. Atos BDS R&D Data Management Echirolles France Univ UPSacaly UVSQ Guyancourt France

Most of the software of modern computer systems come with many configurable parameters that control the system’s behavior and its interaction with the underlying hardware. © 2022, the Author(s), under exclusive ... 详细信息

ISBN: (纸本)9783031220388;9783031220395

关键词： Computer hardware

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Research on Optimization of Modulation and Coding Mode for Power Line Carrier Communication 4

Research on Optimization of Modulation and Coding Mode for P...

引用

4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Liang, Yutu Shi, Zhan Wang, Xiuzhu Wu, Zhentian Power Dispatching Control Center Guangdong Power Grid Co. Ltd. Communication Management Department China Guangdong Electric Power Communication Technology Co. Ltd. Science and Technology Innovation Department China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

Power line carrier is used as the transmission medium of information to complete signal transmission. It has many advantages such as convenient access, no wiring, fast construction speed, and wide distribution range. therefore, low-voltage power line communication is used in smart meter reading, remote control, Internet of things, etc. Has received widespread attention. However, because the power line is not an ideal communication line, its channel has strong time-varying, interference characteristics and Gaussian noise interference, which seriously affects the power line data transmission. In order to transmit high-speed data on the power line, this paper first analyzes the power line channel characteristics and the performance of PLC modulation technology, and then studies wavelet transform and OFDM permutation coding, and proposes a modulation coding based on wavelet transform technology and Reed-Solomon convolutional code. the optimization scheme of the method improves the effectiveness and reliability of system transmission by adopting reasonable signal coding and modulation methods. © 2022 IEEE.

关键词： Wavelet transforms

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the Study of Cramer’s V for Variables Association on Stainless Steels Corrosion Problem 1

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4th international conference on Mathematics, Statistics, and computing Technology, ICMSCT 2023

作者： Afrianti, Yuli Sri Pasaribu, Udjianna Sekteria Ardy, Husaini Statistics Research Division Faculty of Mathematics and Natural Science Institut Teknologi Bandung Bandung Indonesia Material Science and Engineering Research Division Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9789819734504

ISBN: (纸本)9789819734498

Stainless steel (SS) is a type of material used in the Oil and Gas Industry because of its corrosive resistance. A σ phase will be formed if SS is exposed to high temperatures for a long time. the appearance of σ occurs slowly, which is manifested by a change in the color of the SS surface. the presence of σ marked in dark blue indicates that the area has been corroded. this study is a follow-up study from the previous one aiming at testing the association between the variables involved in the SS corrosion problem. the material was processed with a series of treatments in the laboratory to produce images. then, three locations were selected from the images to carry out a circular grid process and calculate the frequency of their color. the frequency listed in the contingency table was the data used to calculate the association between the location and color-based corrosion indicator variable using Chi-square and Cramer’s V. the result showed that although locations A, B, and C were from the different grain, location variables and corrosion indicator variables based on color were dependent. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Location

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data analysis of Global Perceived Stress Scores during Covid-19 4

Data analysis of Global Perceived Stress Scores during Covid...

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4th international conference on Circuits, Control, Communication and computing, I4C 2022

作者： Muttaraju, Chakita Kabber, Anusha Parimala, S. Anagani, Prajwal Srinivasa, Gowri PES University Department of Computer Science and Engineering Bengaluru India PES University PES Center for Pattern Recognition Dept. of CSE Bengaluru India

ISBN: (纸本)9798350397475

the Covid-19 Pandemic that broke out in late December 2019 has had a widespread negative effect on the mental health of people around the world. this work aims to elicit features that had a major influence on mental health during the pandemic to better understand preventive measures and remedial actions that can be taken to help individuals in need. Along with factors such as demographic age, gender, marital status, and employment status, additional information such as the effect of media used as a source of information, coping methods, trust in the country's government, and healthcare organizations was analyzed to find their correlation (if any) to the perceived stress of the individual. Machine Learning techniques such as XGBoost, AdaBoost, Decision Trees, Ordinal regression, k-Nearest Neighbors, Lasso and Ridge regression were used to arrive at a relationship between the perceived stress scores and the features considered. On interpreting results from the different models, we conclude that the main factor influencing stress scores was loneliness followed by features indicating trust in government, compliance with Covid-19 preventive measures and concerns regarding the pandemic. © 2022 IEEE.

关键词： Decision trees

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Research on Machine Learning-based Nowcasting Method for Low Visibility Weather in Urumqi Airport 4

Research on Machine Learning-based Nowcasting Method for Low...

引用

4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Li, Jing Wang, Fan Xue, Kang Hao, Yusong Chengdu China Urumqi International Airport Operation Management Committee of Xinjiang Airport Group Urumqi China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

this paper takes Urumqi Airport as an example, to analyze the visibility of the airport and its impact on normal flight. For the purpose of analysis, the airport's real-time meteorological observation and numerical forecast data is regarded as the analysis field after full consideration of the meteorological observation conditions of the airport, combined with the advantages and disadvantages of mainstream research methods at home and abroad, so that the temporal and spatial characteristic factors causing the low visibility weather at the airport in nowcasting period can be obtained through the analysis and matching of the airport and satellite observation data, to prospect a nowcasting model for low visibility weather in the airport using machine learning algorithms. Due to the addition of multi-channel satellite data, the nowcasting model proposed in this paper can access the visibility evolution information of large scale in space, which provides the basis for the fine monitoring of visibility at the airport. According to the video image monitoring data of airport flight area, the multidimensional and high-frequency quantitative inversion data about the airport visibility can be obtained, which makes up for the lack of low visibility weather monitoring at airport in azimuth and time. © 2022 IEEE.

关键词： Visibility

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Federated Learning for Detecting COVID-19 in Chest CT Images: A Lightweight Federated Learning Approach 4

Federated Learning for Detecting COVID-19 in Chest CT Images...

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4th international conference on Frontiers Technology of Information and Computer, ICFTIC 2022

作者： Lai, Weimin Yan, Qiao College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350321951

the novel coronavirus is spreading rapidly worldwide, and finding an effective and rapid diagnostic method is apriority. Medical data involves patient privacy, and the centralized collection of large amounts of medical data is impossible. Federated learning is a privacy-preserving machine learning paradigm that can be well applied to smart healthcare by coordinating multiple hospitals to perform deep learning training without transmitting data. this paper demonstrates the feasibility of a federated learning approach for detecting COVID-19 through chest CT images. We propose a lightweight federated learning method that normalizes the local training process by globally averaged feature vectors. In the federated training process, the models' parameters do not need to be transmitted, and the local client only uploads the average of the feature vectors of each class. Clients can choose different local models according to their computing capabilities. We performed a comprehensive evaluation using various deep-learning models on COVID-19 chest CT images. the results show that our approach can effectively reduce the communication load of federated learning while having high accuracy for detecting COVID-19 on chest CT images. © 2022 IEEE.

关键词： COVID-19

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Security and Performance Comparison using QR Code through Blockchain Technology 4

Security and Performance Comparison using QR Code through Bl...

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4th international conference on Cognitive computing and Information Processing, CCIP 2022

作者： Dash, Sonali S Rajasekar, V. AMC Engineering College Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665456487

Advances and transitions in healthcare system is constantly changing and acquiring fresh forms. the requirement of modern smart health systems is to protect sensitive patient data from attacks by potential adversaries. the secure data access mechanism ensures that only authorized personnel can access patient's health information. therefore, in distributed method, it protects data in the healthcare system. Here it provides patients and doctors with an efficient and secure access mechanism based on blockchain data collection. In this health system the proposed system can also protect the privacy of patients. Security analysis depends upon architecture to prevent from attacks and maintain integrity of system. In addition, the implementation of system based Ethereum used for feasibility test of proposed system. By hiding private information in the coverage environment in a way that a third party cannot discover this confidential information. In today's era, with the emergence of new technologies, QR codes have become one of the most popular codes. Provide mechanisms for protecting sensitive information QR codes are the most reliable method of hiding data because they do not use error correction levels and because it is difficult to change the encoded information. the process is divided into different categories, and various statistical parameters are used to evaluate its performance. © 2022 IEEE.

关键词： Blockchain

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